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AI Architect - Atlanta, GA | TCS Job


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Job Opportunity Details

Type

Full Time

Salary

Not Telling

Work from home

No

Weekly Working Hours

Not Telling

Positions

Not Telling

Working Location

Atlanta, GA, Atlanta, GA, United States   [ View map ]
Roles & Responsibilities

Key Responsibilities

Enterprise AI Architecture 

  • Define end-to-end architecture for Generative AI, Agentic AI, machine learning, and intelligent automation solutions. 
  • Translate airline business priorities into scalable AI capabilities, reference architectures, solution patterns, and implementation roadmaps. 
  • Design reusable AI services across digital channels, airline operations, IT operations, customer service, engineering, and enterprise functions. 
  • Establish architecture standards for model integration, orchestration, data access, APIs, security, observability, evaluation, and deployment. 
  • Review solution designs and ensure alignment with enterprise standards and target architecture. 

Generative AI and Agentic AI 

  • Architect enterprise-grade LLM solutions using RAG, knowledge grounding, tool integration, and multi-agent orchestration. 
  • Design autonomous and human-in-the-loop workflows with clear controls, approvals, escalations, and auditability. 
  • Define patterns for agent planning, reasoning, state management, memory, function calling, structured outputs, and secure tool access. 
  • Evaluate frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, or equivalent enterprise technologies. 
  • Design reusable components for prompts, tools, workflows, model gateways, evaluation, guardrails, and agent observability. 

Airline Business and Operational Solutions 

  • Partner with airline business and technology teams to identify and prioritize high-value AI opportunities. 
  • Architect solutions for digital customer experience, personalization, operational reliability, disruption management, reservations, customer service, employee assistance, major incident management, intelligent IT operations, engineering productivity, and knowledge management. 
  • Design AI capabilities for high-volume, near-real-time, customer-facing, and operationally critical environments. 
  • Balance innovation and speed with availability, reliability, safety, security, and operational stability. 

Data, Context, and Knowledge Architecture 

  • Design secure data and knowledge architectures that ground AI solutions in trusted enterprise information. 
  • Define patterns for ingestion, chunking, metadata, embeddings, vector search, reranking, retrieval, response validation, and knowledge freshness. 
  • Integrate structured, unstructured, streaming, and operational data through enterprise data platforms, APIs, and event streams. 
  • Partner with data teams to ensure quality, lineage, access control, privacy, and governance for information used by AI systems. 

AWS Cloud and AI Platforms 

  • Architect AI solutions using Amazon Bedrock, SageMaker, OpenSearch, S3, EKS/ECS, Lambda, Step Functions, API Gateway, Glue, Athena, Redshift, Kinesis/MSK, IAM, KMS, Secrets Manager, and CloudWatch. 
  • Evaluate models and services based on quality, security, latency, scalability, portability, reliability, and cost. 
  • Design cloud-native AI platforms that support experimentation, controlled de ployment, enterprise reuse, and model choice. 
  • Integrate third-party and open-source models where appropriate while maintaining enterprise security and governance. 

AI Engineering and Integration 

  • Provide hands-on architecture guidance for Python-based AI services, APIs, microservices, and event-driven applications. 
  • Define secure integration patterns for agents to interact with enterprise applications, APIs, databases, and operational tools. 
  • Establish standards for schema validation, exception handling, retries, fallbacks, rate limits, and human escalation. 
  • Guide teams in building modular, testable, reusable, and maintainable AI components. 

LLMOps, MLOps, Observability, and Production Readiness 

  • Define lifecycle standards for model selection, prompt management, training, fine-tuning, testing, deployment, monitoring, versioning, and retirement. 
  • Establish CI/CD and automated testing for models, prompts, retrieval pipelines, agents, APIs, and supporting services. 
  • Design evaluation frameworks covering accuracy, groundedness, relevance, safety, latency, reliability, operational impact, and cost. 
  • Implement end-to-end tracing and observability for model calls, retrieval decisions, agent execution, tool usage, and failures. 
  • Define production-readiness criteria, rollback approaches, service objectives, support models, and incident-response procedures. 

Responsible AI, Security, and Governance 

  • Embed responsible AI, privacy, cybersecurity, compliance, and risk controls into architecture and delivery. 
  • Define identity, authorization, encryption, data isolation, auditability, secrets management, and sensitive-data protection controls. 
  • Implement guardrails for prompt injection, hallucination, data leakage, unsafe output, and unauthorized tool execution. 
  • Ensure traceability and appropriate human oversight for high-impact or operationally sensitive AI recommendations and actions. 

Technical Leadership and Collaboration 

  • Serve as a trusted AI architecture advisor to business and technology leadership. 
  • Lead architecture reviews, technical workshops, design sessions, and AI use-case assessments. 
  • Provide clear recommendations on technology selection, implementation approach, risks, dependencies, and trade-offs. 
  • Mentor AI engineers, data scientists, software engineers, and solution architects. 
  • Create reference architectures, reusable patterns, standards, playbooks, and contributions to the enterprise AI roadmap. 
Salary Range-$100,000-$150,000 a year

#LI-KR3


TCS Employee Benefits Summary:
Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.a
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

More Information

Application Details

  • Organization Details
    TCS / Tata Consultancy Services
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